Separation of a subcutaneous cardiac signal from a plurality of composite signals

ABSTRACT

A cardiac monitoring and/or stimulation method and systems provide monitoring, defibrillation and/or pacing therapies, including systems detecting and/or treating cardiac arrhythmia. A system includes a housing coupled to a plurality of electrodes configured for subcutaneous non-intrathoracic sensing. A signal processor receives a plurality of composite signals associated with a plurality of sources, separates a signal from the plurality of composite signals using blind source separation, and identifies a cardiac signal. The signal processor may iteratively separate signals from the plurality of composite signals until the cardiac signal is identified. A method of signal separation includes detecting a plurality of composite signals at a plurality of locations, separating a signal using blind source separation, and identifying a cardiac signal. The separation may include a principal component analysis and/or an independent component analysis. The composite signals may be filtered before separation using band-pass filtering, adaptive, or other filters.

RELATED APPLICATIONS

[0001] This application claims the benefit of Provisional PatentApplication Ser. No. 60/462,272, filed on Apr. 11, 2003, to whichpriority is claimed pursuant to 35 U.S.C. §119(e) and which is herebyincorporated herein by reference.

FIELD OF THE INVENTION

[0002] The present invention relates generally to implantable medicaldevices and, more particularly, to subcutaneous cardiac sensing and/orstimulation devices employing cardiac signal separation.

BACKGROUND OF THE INVENTION

[0003] The healthy heart produces regular, synchronized contractions.Rhythmic contractions of the heart are normally controlled by thesinoatrial (SA) node, which is a group of specialized cells located inthe upper right atrium. The SA node is the normal pacemaker of theheart, typically initiating 60-100 heartbeats per minute. When the SAnode is pacing the heart normally, the heart is said to be in normalsinus rhythm.

[0004] If the heart's electrical activity becomes uncoordinated orirregular, the heart is denoted to be arrhythmic. Cardiac arrhythmiaimpairs cardiac efficiency and can be a potential life-threateningevent. Cardiac arrhythmias have a number of etiological sources,including tissue damage due to myocardial infarction, infection, ordegradation of the heart's ability to generate or synchronize theelectrical impulses that coordinate contractions.

[0005] Bradycardia occurs when the heart rhythm is too slow. Thiscondition may be caused, for example, by impaired function of the SAnode, denoted sick sinus syndrome, or by delayed propagation or blockageof the electrical impulse between the atria and ventricles. Bradycardiaproduces a heart rate that is too slow to maintain adequate circulation.

[0006] When the heart rate is too rapid, the condition is denotedtachycardia. Tachycardia may have its origin in either the atria or theventricles. Tachycardias occurring in the atria of the heart, forexample, include atrial fibrillation and atrial flutter. Both conditionsare characterized by rapid contractions of the atria. Besides beinghemodynamically inefficient, the rapid contractions of the atria canalso adversely affect the ventricular rate.

[0007] Ventricular tachycardia occurs, for example, when electricalactivity arises in the ventricular myocardium at a rate more rapid thanthe normal sinus rhythm. Ventricular tachycardia can quickly degenerateinto ventricular fibrillation. Ventricular fibrillation is a conditiondenoted by extremely rapid, uncoordinated electrical activity within theventricular tissue. The rapid and erratic excitation of the ventriculartissue prevents synchronized contractions and impairs the heart'sability to effectively pump blood to the body, which is a fatalcondition unless the heart is returned to sinus rhythm within a fewminutes.

[0008] Implantable cardiac rhythm management systems have been used asan effective treatment for patients with serious arrhythmias. Thesesystems typically include one or more leads and circuitry to sensesignals from one or more interior and/or exterior surfaces of the heart.Such systems also include circuitry for generating electrical pulsesthat are applied to cardiac tissue at one or more interior and/orexterior surfaces of the heart. For example, leads extending into thepatient's heart are connected to electrodes that contact the myocardiumfor sensing the heart's electrical signals and for delivering pulses tothe heart in accordance with various therapies for treating arrhythmias.

[0009] Typical Implantable cardioverter/defibrillators (ICDs) includeone or more endocardial leads to which at least one defibrillationelectrode is connected. Such ICDs are capable of delivering high-energyshocks to the heart, interrupting the ventricular tachyarrhythmia orventricular fibrillation, and allowing the heart to resume normal sinusrhythm. ICDs may also include pacing functionality.

[0010] Although ICDs are very effective at preventing Sudden CardiacDeath (SCD), most people at risk of SCD are not provided withimplantable defibrillators. Primary reasons for this unfortunate realityinclude the limited number of physicians qualified to performtransvenous lead/electrode implantation, a limited number of surgicalfacilities adequately equipped to accommodate such cardiac procedures,and a limited number of the at-risk patient population that may safelyundergo the required endocardial or epicardial lead/electrode implantprocedure. Subcutaneous ICDs are being developed to address theseissues.

[0011] There is a need for improved electrode configurations specific tothe needs of subcutaneous electrode placement and to address the noiseassociated with subcutaneous electrode placement. There is a furtherneed for a method of improving the signal to noise ratio of the cardiacsignal in subcutaneous ICDs. The present invention fulfills these andother needs, and addresses deficiencies in known systems and techniques.

SUMMARY OF THE INVENTION

[0012] The present invention is directed to cardiac monitoring and/orstimulation methods and systems that, in general, provide transthoracicmonitoring, defibrillation therapies, pacing therapies, or a combinationof these capabilities. Embodiments of the present invention includethose directed to subcutaneous cardiac monitoring and/or stimulationmethods and systems that detect and/or treat cardiac activity orarrhythmias.

[0013] According to one embodiment of the invention, a medical systemincludes a housing having a medical device disposed within the housing.The housing is coupled to a plurality of electrodes configured forsubcutaneous non-intrathoracic sensing. A signal processor is coupled tothe plurality of electrodes and configured to receive a plurality ofcomposite signals associated with a plurality of sources sensed by atleast some of the electrodes. The signal processor is further configuredto separate a signal from the plurality of composite signals andidentify the separated signal as a cardiac signal.

[0014] In another embodiment of the present invention, the signalprocessor iteratively separates signals from the plurality of compositesignals until the cardiac signal is identified. The processor mayinclude a filter configured to filter the plurality of composite signalsprior to separating the signal.

[0015] In another aspect of the present invention, a method of signalseparation includes detecting a plurality of composite signals at aplurality of subcutaneous non-intrathoracic locations, the plurality ofcomposite signals associated with a plurality of sources. A signal isseparated, using blind source separation, from the plurality ofcomposite signals, and identified as a cardiac signal. The method mayfurther include a principal component analysis and/or an independentcomponent analysis to perform the blind source separation. The compositesignals may be filtered before separation using band-pass filtering,adaptive, or other filters.

[0016] In another embodiment of the present invention, an estimate ofthe spatial covariance matrix for a composite signal matrix is formedfrom the plurality of composite signals. Independent component analysisand principal component analysis may be performed using the estimate ofthe spatial covariance matrix, producing a set of eigenvalues andassociated eigenvectors. An eigenvector associated with a largestmagnitude eigenvalue may be used to separate the cardiac signal from theplurality of composite signals by multiplying the composite signalmatrix by the eigenvector.

[0017] The signal may be separated iteratively from the plurality ofcomposite signals using an eigenvector associated with a next-largestmagnitude eigenvalue for each iteration, until the cardiac signal isidentified. The cardiac signal may be identified using a local peakdensity (LPD) of the separated signal, wherein the LPD is within apredetermined range. The cardiac signal may also be identified usingbeat detection on the separated signal, wherein a beat rate is within apredetermined range, or by using a local rate of occurrence ofsignificant points in the separated signal, wherein the local rate ofoccurrence is within a predetermined range. The cardiac signal may alsobe identified using a morphology of the separated signal, wherein themorphology satisfies a physiological characteristic.

[0018] The above summary of the present invention is not intended todescribe each embodiment or every implementation of the presentinvention. Advantages and attainments, together with a more completeunderstanding of the invention, will become apparent and appreciated byreferring to the following detailed description and claims taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019]FIGS. 1A and 1B are views of a transthoracic cardiac sensingand/or stimulation device as implanted in a patient in accordance withan embodiment of the present invention;

[0020]FIG. 1C is a block diagram illustrating various components of atransthoracic cardiac sensing and/or stimulation device in accordancewith an embodiment of the present invention;

[0021]FIG. 1D is a block diagram illustrating various processing anddetection components of a transthoracic cardiac sensing and/orstimulation device in accordance with an embodiment of the presentinvention;

[0022]FIG. 2 is a diagram illustrating components of a transthoraciccardiac sensing and/or stimulation device including an electrode arrayin accordance with an embodiment of the present invention;

[0023]FIG. 3 is a block diagram illustrating uses of signal separationin accordance with the present invention;

[0024]FIG. 4 is a block diagram of a cardiac sensing methodologyincorporating signal separation in accordance with the presentinvention;

[0025]FIG. 5 is a block diagram of a signal separation process inaccordance with the present invention;

[0026]FIG. 6 is an expanded block diagram of the process illustrated inFIG. 5, illustrating an iterative independent component analysis inaccordance with the present invention; and

[0027]FIG. 7 is a graph illustrating the results of a signal separationprocess in accordance with the present invention.

[0028] While the invention is amenable to various modifications andalternative forms, specifics thereof have been shown by way of examplein the drawings and will be described in detail below. It is to beunderstood, however, that the intention is not to limit the invention tothe particular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

[0029] In the following description of the illustrated embodiments,references are made to the accompanying drawings, which form a parthereof, and in which is shown by way of illustration, variousembodiments in which the invention may be practiced. It is to beunderstood that other embodiments may be utilized, and structural andfunctional changes may be made without departing from the scope of thepresent invention.

[0030] An implanted device according to the present invention mayinclude one or more of the features, structures, methods, orcombinations thereof described hereinbelow. For example, a cardiacmonitor or a cardiac stimulator may be implemented to include one ormore of the advantageous features and/or processes described below. Itis intended that such a monitor, stimulator, or other implanted orpartially implanted device need not include all of the featuresdescribed herein, but may be implemented to include selected featuresthat provide for unique structures and/or functionality. Such a devicemay be implemented to provide a variety of therapeutic or diagnosticfunctions.

[0031] In general terms, an implantable noise canceling lead system maybe used with a subcutaneous cardiac monitoring and/or stimulationdevice. One such device is an implantable transthoracic cardiac sensingand/or stimulation (ITCS) device that may be implanted under the skin inthe chest region of a patient. The ITCS device may, for example, beimplanted subcutaneously such that all or selected elements of thedevice are positioned on the patient's front, back, side, or other bodylocations suitable for sensing cardiac activity and delivering cardiacstimulation therapy. It is understood that elements of the ITCS devicemay be located at several different body locations, such as in thechest, abdominal, or subclavian region with electrode elementsrespectively positioned at different regions near, around, in, or on theheart.

[0032] The primary housing (e.g., the active or non-active can) of theITCS device, for example, may be configured for positioning outside ofthe rib cage at an intercostal or subcostal location, within theabdomen, or in the upper chest region (e.g., subclavian location, suchas above the third rib). In one implementation, one or more electrodesmay be located on the primary housing and/or at other locations about,but not in direct contact with the heart, great vessel or coronaryvasculature.

[0033] In another implementation, one or more noise canceling leadsincorporating electrodes may be located in direct contact with theheart, great vessel or coronary vasculature, such as via one or moreleads implanted by use of conventional transvenous delivery approaches.In a further implementation, for example, one or more subcutaneous noisecanceling electrode subsystems or electrode arrays may be used to sensecardiac activity and deliver cardiac stimulation energy in an ITCSdevice configuration employing an active can or a configurationemploying a non-active can. Electrodes may be situated at anteriorand/or posterior locations relative to the heart. Examples of noisecanceling subcutaneous electrodes and electrode arrays are described incommonly owned US Patent Application entitled “Noise Canceling CardiacElectrodes,” filed concurrently herewith under Attorney Docket NumberGUID.603PA, which is hereby incorporated herein by reference.

[0034] Certain configurations illustrated herein are generally describedas capable of implementing various functions traditionally performed byan implantable cardioverter/defibrillator (ICD), and may operate innumerous cardioversion/defibrillation modes as are known in the art.Exemplary ICD circuitry, structures and functionality, aspects of whichmay be incorporated in an ITCS device of a type that may benefit fromnoise canceling electrode configurations, are disclosed in commonlyowned U.S. Pat. Nos. 5,133,353; 5,179,945; 5,314,459; 5,318,597;5,620,466; and 5,662,688, which are hereby incorporated herein byreference in their respective entireties.

[0035] In particular configurations, systems and methods may performfunctions traditionally performed by pacemakers, such as providingvarious pacing therapies as are known in the art, in addition tocardioversion/defibrillation therapies. Exemplary pacemaker circuitry,structures and functionality, aspects of which may be incorporated in anITCS device of a type that may benefit from signal separation, aredisclosed in commonly owned U.S. Pat. Nos. 4,562,841; 5,284,136;5,376,106; 5,036,849; 5,540,727; 5,836,987; 6,044,298; and 6,055,454,which are hereby incorporated herein by reference in their respectiveentireties. It is understood that ITCS device configurations may providefor non-physiologic pacing support in addition to, or to the exclusionof, bradycardia and/or anti-tachycardia pacing therapies.

[0036] An ITCS device in accordance with the present invention mayimplement diagnostic and/or monitoring functions as well as providecardiac stimulation therapy. Exemplary cardiac monitoring circuitry,structures and functionality, aspects of which may be incorporated in anITCS device of a type that may benefit from noise canceling electrodeconfigurations, are disclosed in commonly owned U.S. Pat. Nos.5,313,953; 5,388,578; and 5,411,031, which are hereby incorporatedherein by reference in their respective entireties.

[0037] An ITCS device may be used to implement various diagnosticfunctions, which may involve performing rate-based, pattern andrate-based, and/or morphological tachyarrhythmia discriminationanalyses. Subcutaneous, cutaneous, and/or external sensors may beemployed to acquire physiologic and non-physiologic information forpurposes of enhancing tachyarrhythmia detection and termination. It isunderstood that configurations, features, and combination of featuresdescribed in the instant disclosure may be implemented in a wide rangeof implantable medical devices, and that such embodiments and featuresare not limited to the particular devices described herein.

[0038] Referring now to FIGS. 1A and 1B of the drawings, there is showna configuration of a transthoracic cardiac sensing and/or stimulation(ITCS) device having components implanted in the chest region of apatient at different locations. In the particular configuration shown inFIGS. 1A and 1B, the ITCS device includes a housing 102 within whichvarious cardiac sensing, detection, processing, and energy deliverycircuitry may be housed. It is understood that the components andfunctionality depicted in the figures and described herein may beimplemented in hardware, software, or a combination of hardware andsoftware. It is further understood that the components and functionalitydepicted as separate or discrete blocks/elements in the figures may beimplemented in combination with other components and functionality, andthat the depiction of such components and functionality in individual orintegral form is for purposes of clarity of explanation, and not oflimitation.

[0039] Communications circuitry is disposed within the housing 102 forfacilitating communication between the ITCS device and an externalcommunication device, such as a portable or bed-side communicationstation, patient-carried/worn communication station, or externalprogrammer, for example. The communications circuitry may alsofacilitate unidirectional or bidirectional communication with one ormore external, cutaneous, or subcutaneous physiologic or non-physiologicsensors. The housing 102 is typically configured to include one or moreelectrodes (e.g., can electrode and/or indifferent electrode). Althoughthe housing 102 is typically configured as an active can, it isappreciated that a non-active can configuration may be implemented, inwhich case at least two electrodes spaced apart from the housing 102 areemployed.

[0040] In the configuration shown in FIGS. 1A and 1B, a subcutaneouselectrode 104 may be positioned under the skin in the chest region andsituated distal from the housing 102. The subcutaneous and, ifapplicable, housing electrode(s) may be positioned about the heart atvarious locations and orientations, such as at various anterior and/orposterior locations relative to the heart. The subcutaneous electrode104 is coupled to circuitry within the housing 102 via a lead assembly106. One or more conductors (e.g., coils or cables) are provided withinthe lead assembly 106 and electrically couple the subcutaneous electrode104 with circuitry in the housing 102. One or more sense, sense/pace ordefibrillation electrodes may be situated on the elongated structure ofthe electrode support, the housing 102, and/or the distal electrodeassembly (shown as subcutaneous electrode 104 in the configuration shownin FIGS. 1A and 1B).

[0041] In one configuration, the lead assembly 106 is generally flexibleand has a construction similar to conventional implantable, medicalelectrical leads (e.g., defibrillation leads or combineddefibrillation/pacing leads). In another configuration, the leadassembly 106 is constructed to be somewhat flexible, yet has an elastic,spring, or mechanical memory that retains a desired configuration afterbeing shaped or manipulated by a clinician. For example, the leadassembly 106 may incorporate a gooseneck or braid system that may bedistorted under manual force to take on a desired shape. In this manner,the lead assembly 106 may be shape-fit to accommodate the uniqueanatomical configuration of a given patient, and generally retains acustomized shape after implantation. Shaping of the lead assembly 106according to this configuration may occur prior to, and during, ITCSdevice implantation.

[0042] In accordance with a further configuration, the lead assembly 106includes a rigid electrode support assembly, such as a rigid elongatedstructure that positionally stabilizes the subcutaneous electrode 104with respect to the housing 102. In this configuration, the rigidity ofthe elongated structure maintains a desired spacing between thesubcutaneous electrode 104 and the housing 102, and a desiredorientation of the subcutaneous electrodel 104/housing 102 relative tothe patient's heart. The elongated structure may be formed from astructural plastic, composite or metallic material, and comprises, or iscovered by, a biocompatible material. Appropriate electrical isolationbetween the housing 102 and subcutaneous electrode 104 is provided incases where the elongated structure is formed from an electricallyconductive material, such as metal.

[0043] In one configuration, the rigid electrode support assembly andthe housing 102 define a unitary structure (e.g., a singlehousing/unit). The electronic components and electrodeconductors/connectors are disposed within or on the unitary ITCS devicehousing/electrode support assembly. At least two electrodes aresupported on the unitary structure near opposing ends of thehousing/electrode support assembly. The unitary structure may have anarcuate or angled shape, for example.

[0044] According to another configuration, the rigid electrode supportassembly defines a physically separable unit relative to the housing102. The rigid electrode support assembly includes mechanical andelectrical couplings that facilitate mating engagement withcorresponding mechanical and electrical couplings of the housing 102.For example, a header block arrangement may be configured to includeboth electrical and mechanical couplings that provide for mechanical andelectrical connections between the rigid electrode support assembly andhousing 102. The header block arrangement may be provided on the housing102 or the rigid electrode support assembly. Alternatively, amechanical/electrical coupler may be used to establish mechanical andelectrical connections between the rigid electrode support assembly andhousing 102. In such a configuration, a variety of different electrodesupport assemblies of varying shapes, sizes, and electrodeconfigurations may be made available for physically and electricallyconnecting to a standard ITCS device housing 102.

[0045] It is noted that the electrodes and the lead assembly 106 may beconfigured to assume a variety of shapes. For example, the lead assembly106 may have a wedge, chevron, flattened oval, or a ribbon shape, andthe subcutaneous electrode 104 may comprise a number of spacedelectrodes, such as an array or band of electrodes. Moreover, two ormore subcutaneous electrodes 104 may be mounted to multiple electrodesupport assemblies 106 to achieve a desired spaced relationship amongstsubcutaneous electrodes 104.

[0046] An ITCS device may incorporate circuitry, structures andfunctionality of the subcutaneous implantable medical devices disclosedin commonly owned U.S. Pat. Nos. 5,203,348; 5,230,337; 5,360,442;5,366,496; 5,397,342; 5,391,200; 5,545,202; 5,603,732; and 5,916,243,which are hereby incorporated herein by reference in their respectiveentireties.

[0047]FIG. 1C is a block diagram depicting various components of an ITCSdevice in accordance with one configuration. According to thisconfiguration, the ITCS device incorporates a processor-based controlsystem 205 which includes a micro-processor 206 coupled to appropriatememory (volatile and non-volatile) 209, it being understood that anylogic-based control architecture may be used. The control system 205 iscoupled to circuitry and components to sense, detect, and analyzeelectrical signals produced by the heart and deliver electricalstimulation energy to the heart under predetermined conditions to treatcardiac arrhythmias. In certain configurations, the control system 205and associated components also provide pacing therapy to the heart. Theelectrical energy delivered by the ITCS device may be in the form of lowenergy pacing pulses or high-energy pulses for cardioversion ordefibrillation.

[0048] Cardiac signals are sensed using the subcutaneous electrode(s)214 and the can or indifferent electrode 207 provided on the ITCS devicehousing. Cardiac signals may also be sensed using only the subcutaneouselectrodes 214, such as in a non-active can configuration. As such,unipolar, bipolar, or combined unipolar/bipolar electrode configurationsas well as multi-element noise canceling electrodes and combinations ofnoise canceling and standard electrodes may be employed. The sensedcardiac signals are received by sensing circuitry 204, which includessense amplification circuitry and may also include filtering circuitryand an analog-to-digital (A/D) converter. The sensed cardiac signalsprocessed by the sensing circuitry 204 may be received by noisereduction circuitry 203, which may further reduce noise before signalsare sent to the detection circuitry 202.

[0049] Noise reduction circuitry 203 may also be incorporated aftersensing circuitry 202 in cases where high power or computationallyintensive noise reduction algorithms are required. The noise reductioncircuitry 203, by way of amplifiers used to perform operations with theelectrode signals, may also perform the function of the sensingcircuitry 204. Combining the functions of sensing circuitry 204 andnoise reduction circuitry 203 may be useful to minimize the necessarycomponentry and lower the power requirements of the system.

[0050] In the illustrative configuration shown in FIG. 1C, the detectioncircuitry 202 is coupled to, or otherwise incorporates, noise reductioncircuitry 203. The noise reduction circuitry 203 operates to improve theSNR of sensed cardiac signals by removing noise content of the sensedcardiac signals introduced from various sources. Typical types oftransthoracic cardiac signal noise includes electrical noise and noiseproduced from skeletal muscles, for example. A number of methodologiesfor improving the SNR of sensed cardiac signals in the presence ofskeletal muscular induced noise, including signal separation techniquesincorporating combinations of electrodes and noise cancelingmulti-element electrodes, are described hereinbelow.

[0051] Detection circuitry 202 typically includes a signal processorthat coordinates analysis of the sensed cardiac signals and/or othersensor inputs to detect cardiac arrhythmias, such as, in particular,tachyarrhythmia. Rate based and/or morphological discriminationalgorithms may be implemented by the signal processor of the detectioncircuitry 202 to detect and verify the presence and severity of anarrhythmic episode. Exemplary arrhythmia detection and discriminationcircuitry, structures, and techniques, aspects of which may beimplemented by an ITCS device of a type that may benefit from noisecanceling electrode configurations, are disclosed in commonly owned U.S.Pat. Nos. 5,301,677 and 6,438,410, which are hereby incorporated hereinby reference in their respective entireties. Arrhythmia detectionmethodologies particularly well suited for implementation insubcutaneous cardiac monitoring and/or stimulation systems are describedhereinbelow.

[0052] The detection circuitry 202 communicates cardiac signalinformation to the control system 205. Memory circuitry 209 of thecontrol system 205 contains parameters for operating in various sensing,defibrillation, and, if applicable, pacing modes, and stores dataindicative of cardiac signals received by the detection circuitry 202.The memory circuitry 209 may also be configured to store historical ECGand therapy data, which may be used for various purposes and transmittedto an external receiving device as needed or desired.

[0053] In certain configurations, the ITCS device may includediagnostics circuitry 210. The diagnostics circuitry 210 typicallyreceives input signals from the detection circuitry 202 and the sensingcircuitry 204. The diagnostics circuitry 210 provides diagnostics datato the control system 205, it being understood that the control system205 may incorporate all or part of the diagnostics circuitry 210 or itsfunctionality. The control system 205 may store and use informationprovided by the diagnostics circuitry 210 for a variety of diagnosticspurposes. This diagnostic information may be stored, for example,subsequent to a triggering event or at predetermined intervals, and mayinclude system diagnostics, such as power source status, therapydelivery history, and/or patient diagnostics. The diagnostic informationmay take the form of electrical signals or other sensor data acquiredimmediately prior to therapy delivery.

[0054] According to a configuration that provides cardioversion anddefibrillation therapies, the control system 205 processes cardiacsignal data received from the detection circuitry 202 and initiatesappropriate tachyarrhythmia therapies to terminate cardiac arrhythmicepisodes and return the heart to normal sinus rhythm. The control system205 is coupled to shock therapy circuitry 216. The shock therapycircuitry 216 is coupled to the subcutaneous electrode(s) 214 and thecan or indifferent electrode 207 of the ITCS device housing. Uponcommand, the shock therapy circuitry 216 delivers cardioversion anddefibrillation stimulation energy to the heart in accordance with aselected cardioversion or defibrillation therapy. In a lesssophisticated configuration, the shock therapy circuitry 216 iscontrolled to deliver defibrillation therapies, in contrast to aconfiguration that provides for delivery of both cardioversion anddefibrillation therapies. Exemplary ICD high energy delivery circuitry,structures and functionality, aspects of which may be incorporated in anITCS device of a type that may benefit from aspects of the presentinvention are disclosed in commonly owned U.S. Pat. Nos. 5,372,606;5,411,525; 5,468,254; and 5,634,938, which are hereby incorporatedherein by reference in their respective entireties.

[0055] In accordance with another configuration, an ITCS device mayincorporate a cardiac pacing capability in addition to cardioversionand/or defibrillation capabilities. As is shown in dotted lines in FIG.1C, the ITCS device may include pacing therapy circuitry 230 which iscoupled to the control system 205 and the subcutaneous andcan/indifferent electrodes 214, 207. Upon command, the pacing therapycircuitry delivers pacing pulses to the heart in accordance with aselected pacing therapy. Control signals, developed in accordance with apacing regimen by pacemaker circuitry within the control system 205, areinitiated and transmitted to the pacing therapy circuitry 230 wherepacing pulses are generated. A pacing regimen may be modified by thecontrol system 205.

[0056] A number of cardiac pacing therapies may be useful in atransthoracic cardiac monitoring and/or stimulation device. Such cardiacpacing therapies may be delivered via the pacing therapy circuitry 230as shown in FIG. 1C. Alternatively, cardiac pacing therapies may bedelivered via the shock therapy circuitry 216, which effectivelyobviates the need for separate pacemaker circuitry.

[0057] The ITCS device shown in FIG. 1C may be configured to receivesignals from one or more physiologic and/or non-physiologic sensors.Depending on the type of sensor employed, signals generated by thesensors may be communicated to transducer circuitry coupled directly tothe detection circuitry 202 or indirectly via the sensing circuitry 204.It is noted that certain sensors may transmit sense data to the controlsystem 205 without processing by the detection circuitry 202.

[0058] Communications circuitry 218 is coupled to the microprocessor 206of the control system 205. The communications circuitry 218 allows theITCS device to communicate with one or more receiving devices or systemssituated external to the ITCS device. By way of example, the ITCS devicemay communicate with a patient-worn, portable or bedside communicationsystem via the communications circuitry 218. In one configuration, oneor more physiologic or non-physiologic sensors (subcutaneous, cutaneous,or external of patient) may be equipped with a short-range wirelesscommunication interface, such as an interface conforming to a knowncommunications standard, such as Bluetooth or IEEE 802 standards. Dataacquired by such sensors may be communicated to the ITCS device via thecommunications circuitry 218. It is noted that physiologic ornon-physiologic sensors equipped with wireless transmitters ortransceivers may communicate with a receiving system external of thepatient.

[0059] The communications circuitry 218 may allow the ITCS device tocommunicate with an external programmer. In one configuration, thecommunications circuitry 218 and the programmer unit (not shown) use awire loop antenna and a radio frequency telemetric link, as is known inthe art, to receive and transmit signals and data between the programmerunit and communications circuitry 218. In this manner, programmingcommands and data are transferred between the ITCS device and theprogrammer unit during and after implant. Using a programmer, aphysician is able to set or modify various parameters used by the ITCSdevice. For example, a physician may set or modify parameters affectingsensing, detection, pacing, and defibrillation functions of the ITCSdevice, including pacing and cardioversion/defibrillation therapy modes.

[0060] Typically, the ITCS device is encased and hermetically sealed ina housing suitable for implanting in a human body as is known in theart. Power to the ITCS device is supplied by an electrochemical powersource 220 housed within the ITCS device. In one configuration, thepower source 220 includes a rechargeable battery. According to thisconfiguration, charging circuitry is coupled to the power source 220 tofacilitate repeated non-invasive charging of the power source 220. Thecommunications circuitry 218, or separate receiver circuitry, isconfigured to receive RF energy transmitted by an external RF energytransmitter. The ITCS device may, in addition to a rechargeable powersource, include a non-rechargeable battery. It is understood that arechargeable power source need not be used, in which case a long-lifenon-rechargeable battery is employed.

[0061]FIG. 1D illustrates a configuration of detection circuitry 302 ofan ITCS device, which includes one or both of rate detection circuitry310 and morphological analysis circuitry 312. Detection and verificationof arrhythmias may be accomplished using rate-based discriminationalgorithms as known in the art implemented by the rate detectioncircuitry 310. Arrhythmic episodes may also be detected and verified bymorphology-based analysis of sensed cardiac signals as is known in theart. Tiered or parallel arrhythmia discrimination algorithms may also beimplemented using both rate-based and morphologic-based approaches.Further, a rate and pattern-based arrhythmia detection anddiscrimination approach may be employed to detect and/or verifyarrhythmic episodes, such as the approach disclosed in U.S. Pat. Nos.6,487,443; 6,259,947; 6,141,581; 5,855,593; and 5,545,186, which arehereby incorporated herein by reference in their respective entireties.

[0062] The detection circuitry 302, which is coupled to a microprocessor306, may be configured to incorporate, or communicate with, specializedcircuitry for processing sensed cardiac signals in manners particularlyuseful in a transthoracic cardiac sensing and/or stimulation device. Asis shown by way of example in FIG. 1D, the detection circuitry 302 mayreceive information from multiple physiologic and non-physiologicsensors. As illustrated, transthoracic acoustics may be monitored usingan appropriate acoustic sensor. Heart sounds, for example, may bedetected and processed by cardiac acoustic processing circuitry 318 fora variety of purposes. The acoustics data is transmitted to thedetection circuitry 302, via a hardwire or wireless link, and used toenhance cardiac signal detection. For example, acoustics may be used todiscriminate normal cardiac sinus rhythm with electrical noise frompotentially lethal arrhythmias, such as ventricular tachycardia orventricular fibrillation.

[0063] The detection circuitry 302 may also receive information from oneor more sensors that monitor skeletal muscle activity. In addition tocardiac activity signals, transthoracic electrodes readily detectskeletal muscle signals. Such skeletal muscle signals may be used todetermine the activity level of the patient. In the context of cardiacsignal detection, such skeletal muscle signals are considered artifactsof the cardiac activity signal, which may be viewed as noise. Processingcircuitry 316 receives signals from one or more skeletal muscle sensors,and transmits processed skeletal muscle signal data to the detectioncircuitry 302. This data may be used to discriminate normal cardiacsinus rhythm with skeletal muscle noise from cardiac arrhythmias.

[0064] As was previously discussed, the detection circuitry 302 iscoupled to, or otherwise incorporates, noise-processing circuitry 314.The noise processing circuitry 314 processes sensed cardiac signals toimprove the SNR of sensed cardiac signals by reducing noise content ofthe sensed cardiac signals.

[0065] The components, functionality, and structural configurationsdepicted in FIGS. 1A-1D are intended to provide an understanding ofvarious features and combination of features that may be incorporated inan ITCS device. It is understood that a wide variety of ITCS and otherimplantable cardiac monitoring and/or stimulation device configurationsare contemplated, ranging from relatively sophisticated to relativelysimple designs. As such, particular ITCS or cardiac monitoring and/orstimulation device configurations may include particular features asdescribed herein, while other such device configurations may excludeparticular features described herein.

[0066] In accordance with embodiments of the invention, an ITCS devicemay be implemented to include a subcutaneous electrode system thatprovides for one or both of cardiac sensing and arrhythmia therapydelivery. According to one approach, an ITCS device may be implementedas a chronically implantable system that performs monitoring, diagnosticand/or therapeutic functions. The ITCS device may automatically detectand treat cardiac arrhythmias. In one configuration, the ITCS deviceincludes a pulse generator and one or more electrodes that are implantedsubcutaneously in the chest region of the body, such as in the anteriorthoracic region of the body. The ITCS device may be used to provideatrial and ventricular therapy for bradycardia and tachycardiaarrhythmias. Tachyarrhythmia therapy may include cardioversion,defibrillation and anti-tachycardia pacing (ATP), for example, to treatatrial or ventricular tachycardia or fibrillation. Bradycardia therapymay include temporary post-shock pacing for bradycardia or asystole.Methods and systems for implementing post-shock pacing for bradycardiaor asystole are described in commonly owned U.S. Patent Applicationentitled “Subcutaneous Cardiac Stimulator Employing Post-ShockTransthoracic Asystole Prevention Pacing, Ser. No. 10/377,274, filed onFeb. 28, 2003, which is incorporated herein by reference in itsentirety.

[0067] In one configuration, an ITCS device according to one approachmay utilize conventional pulse generator and subcutaneous electrodeimplant techniques. The pulse generator device and electrodes may bechronically implanted subcutaneously. Such an ITCS may be used toautomatically detect and treat arrhythmias similarly to conventionalimplantable systems. In another configuration, the ITCS device maycomprise a unitary structure (e.g., a single housing/unit). Theelectronic components and electrode conductors/connectors are disposedwithin or on the unitary ITCS device housing/electrode support assembly.

[0068] The ITCS device contains the electronics and may be similar to aconventional implantable defibrillator. High voltage shock therapy maybe delivered between two or more electrodes, one of which may be thepulse generator housing (e.g., can), placed subcutaneously in thethoracic region of the body.

[0069] Additionally or alternatively, the ITCS device may also providelower energy electrical stimulation for bradycardia therapy. The ITCSdevice may provide brady pacing similarly to a conventional pacemaker.The ITCS device may provide temporary post-shock pacing for bradycardiaor asystole. Sensing and/or pacing may be accomplished using sense/paceelectrodes positioned on an electrode subsystem also incorporating shockelectrodes, or by separate electrodes implanted subcutaneously.

[0070] The ITCS device may detect a variety of physiological signalsthat may be used in connection with various diagnostic, therapeutic ormonitoring implementations. For example, the ITCS device may includesensors or circuitry for detecting respiratory system signals, cardiacsystem signals, and signals related to patient activity. In oneembodiment, the ITCS device senses intrathoracic impedance, from whichvarious respiratory parameters may be derived, including, for example,respiratory tidal volume and minute ventilation. Sensors and associatedcircuitry may be incorporated in connection with an ITCS device fordetecting one or more body movement or body position related signals.For example, accelerometers and GPS devices may be employed to detectpatient activity, patient location, body orientation, or torso position.

[0071] The ITCS device may be used within the structure of an advancedpatient management (APM) system. Advanced patient management systems mayallow physicians to remotely and automatically monitor cardiac andrespiratory functions, as well as other patient conditions. In oneexample, implantable cardiac rhythm management systems, such as cardiacpacemakers, defibrillators, and resynchronization devices, may beequipped with various telecommunications and information technologiesthat enable real-time data collection, diagnosis, and treatment of thepatient. Various embodiments described herein may be used in connectionwith advanced patient management. Methods, structures, and/or techniquesdescribed herein, which may be adapted to provide for remotepatient/device monitoring, diagnosis, therapy, or other APM relatedmethodologies, can incorporate features of one or more of the followingreferences: U.S. Pat. Nos. 6,221,011; 6,270,457; 6,277,072; 6,280,380;6,312,378; 6,336,903; 6,358,203; 6,368,284; 6,398,728; and 6,440,066,which are hereby incorporated herein by reference.

[0072] An ITCS device according to one approach provides an easy toimplant therapeutic, diagnostic or monitoring system. The ITCS systemmay be implanted without the need for intravenous or intrathoracicaccess, providing a simpler, less invasive implant procedure andminimizing lead and surgical complications. In addition, this systemwould have advantages for use in patients for whom transvenous leadsystems cause complications. Such complications include, but are notlimited to, surgical complications, infection, insufficient vesselpatency, complications associated with the presence of artificialvalves, and limitations in pediatric patients due to patient growth,among others. An ITCS system according to this approach is distinct fromconventional approaches in that it is preferably configured to include acombination of two or more electrode subsystems that are implantedsubcutaneously in the anterior thorax.

[0073] In one configuration, as is illustrated in FIG. 2, electrodesubsystems of an ITCS system are arranged about a patient's heart 510.The ITCS system includes a first electrode subsystem, comprising a canelectrode 502, and a second electrode subsystem 504 that includes atleast two electrodes or at least one multi-element electrode. The secondelectrode subsystem 504 may comprise a number of electrodes used forsensing and/or electrical stimulation.

[0074] In various configurations, the second electrode subsystem 504 maycomprise a combination of electrodes. The combination of electrodes ofthe second electrode subsystem 504 may include coil electrodes, tipelectrodes, ring electrodes, multi-element coils, spiral coils, spiralcoils mounted on non-conductive backing, screen patch electrodes, andother electrode configurations as will be described below. A suitablenon-conductive backing material is silicone rubber, for example.

[0075] The can electrode 502 is positioned on the housing 501 thatencloses the ITCS device electronics. In one embodiment, the canelectrode 502 comprises the entirety of the external surface of housing501. In other embodiments, various portions of the housing 501 may beelectrically isolated from the can electrode 502 or from tissue. Forexample, the active area of the can electrode 502 may comprise all or aportion of either the anterior or posterior surface of the housing 501to direct current flow in a manner advantageous for cardiac sensingand/or stimulation.

[0076] In accordance with one embodiment, the housing 501 may resemblethat of a conventional implantable ICD, is approximately 20-100 cc involume, with a thickness of 0.4 to 2 cm and with a surface area on eachface of approximately 30 to 100 cm₂. As previously discussed, portionsof the housing may be electrically isolated from tissue to optimallydirect current flow. For example, portions of the housing 501 may becovered with a non-conductive, or otherwise electrically resistive,material to direct current flow. Suitable non-conductive materialcoatings include those formed from silicone rubber, polyurethane, orparylene, for example.

[0077] In addition, or alternatively, all or portions of the housing 501may be treated to change the electrical conductivity characteristicsthereof for purposes of optimally directing current flow. Various knowntechniques may be employed to modify the surface conductivitycharacteristics of the housing 501, such as by increasing or decreasingsurface conductivity, to optimize current flow. Such techniques mayinclude those that mechanically or chemically alter the surface of thehousing 501 to achieve desired electrical conductivity characteristics.

[0078] As was discussed above, cardiac signals collected fromsubcutaneously implanted electrodes may be corrupted by noise. Inaddition, certain noise sources have frequency characteristics similarto those of the cardiac signal. Such noise may lead to over sensing andspurious shocks. Due to the possibility of relatively high amplitude ofthe noise signal and overlapping frequency content, filtering alone doesnot lead to complete suppression of the noise. In addition, filterperformance is not generally sufficiently robust against the entireclass of noises encountered. Further, known adaptive filteringapproaches require a reference signal that is often unknown forsituations when a patient experiences VF or high amplitude noise.

[0079] An ITCS device according to the present invention may beimplemented to include a noise rejection/reduction capability to improvenoise rejection of cardiac signals sensed by subcutaneous electrodes.This noise rejection/reduction approach advantageously reduces the riskof false positives for detection algorithms by improving the signal tonoise ratio of the cardiac signal.

[0080] In accordance with one approach of the present invention, an ITCSdevice may be implemented to separate cardiac signals from noise in arobust manner using a blind source separation (BSS) technique. It isunderstood that all or certain aspects of the BSS technique describedbelow may be implemented in a device or system (implantable ornon-implantable) other than an ITCS device, and that the description ofBSS techniques implemented in an ITCS device is provided for purposes ofillustration, and not of limitation. For example, algorithms thatimplement a BSS technique as described below may be implemented for useby an implanted processor or a non-implanted processor, such as aprocessor of a programmer or computer.

[0081] Referring now to FIGS. 3 through 6, subcutaneous cardiac sensingand/or stimulation devices and methods employing cardiac signalseparation are described in accordance with the present invention. Themain principle of signal separation works on the premise that spatiallydistributed electrodes collect components of a signal from a commonorigin (e.g., the heart) with the result that these components will bestrongly correlated to each other in time. In addition, these componentswill also be weakly correlated to components of another origin (e.g.,noise). The ITCS device may be implemented to separate these componentsaccording to their sources. To achieve this, the methods and algorithmsillustrated in FIGS. 3 through 6 may be implemented.

[0082]FIG. 3 illustrates a source separation system 125 in accordancewith the present invention. A source separation process 414 isperformed, providing a separated signal 419. The separated signal 419 isavailable for a variety of uses 420, such as, for example, arrhythmiadetection, SVR (Supra-Ventricular Rhythm) confirmation, NSR (NormalSinus Rhythm) confirmation, arrhythmia classification or other use.

[0083]FIG. 4 illustrates a signal source separation methodology 150 inaccordance with the present invention. After initiating 402 themethodology, a signal record process begins 404. During the signalrecord event 404, one or more electrode signals are recorded for laterprocessing, such as by signal source separation processing. Therecording may be continuous or performed for a given period of time. Atblock 406, a determination is made as to the presence or absence of anSVR using technology known in the art. If an SVR is detected, no otheraction is necessary, and recording and evaluation for SVR continues.

[0084] If SVR is absent, it is desirable to determine whether an adversecardiac condition exists, necessitating intervention, or whether thereis simply a spurious signal loss or other event not necessitatingintervention. A loss of SVR at decision 406 initiates a separationprocess 100, which will be described in greater detail below. After theseparation process 100 and any intervention steps deemed necessary arecompleted, a determination 408 is made as to whether other processing isnecessary. If no further processing is necessary, the recording process404 continues. If further processing is necessary, such additionalprocessing 410 is performed, along with any further action associatedwith processing 410, and then recording 404 continues.

[0085]FIG. 5 illustrates another embodiment of a signal sourceseparation process 100 in accordance with the present invention. A setof composite signals, including at least two and up to n signals, areselected for separation, where n is an integer. Each electrode providesa composite signal associated with an unknown number of sources.Pre-processing and/or pre-filtering 412 can be performed on each of thecomposite signals. It may be advantageous to filter each compositesignal using the same filtering function. Source separation 414 isperformed, providing at least one separated signal. The separated signalcan then be used 420 for some specified purpose, such as, for example,to confirm a normal sinus rhythm, determine a cardiac condition, definea noise signal, or other desired use.

[0086] If a treatment is desired, an appropriate treatment or therapy418 is performed. If continued source separation is desired, the processreturns to perform such source separation 414 and may iterativelyseparate 416 more signals until a desired signal is found, or allsignals are separated.

[0087]FIG. 6 illustrates further embodiments of a signal sourceseparation process in greater detail, including some optional elements.Entry of the process at block 422 provides access to a pre-processingfacility 412, illustrated here as including a covariance matrixcomputation block 424 and/or a pre-filtering block 426 such as, forexample, a band-pass filtering block. The composite signals processed atpre-processing block 412 are provided to a signal source separationblock 415, which can include functionality of the source separationblock 414 and iterative source separation block 416 shown in FIG. 5.

[0088] The signal source separation block 415 includes a principalcomponent analysis block 428, which produces an associated set ofeigenvectors and eigenvalues using a covariance matrix or compositesignals provided by pre-processing block 412. A determination 430 ismade as to whether one eigenvalue is significantly larger than anyothers in the set, making the dimension associated with this eigenvaluea likely candidate for association with the cardiac signal. If such acandidate is identified at block 430, the candidate signal mayimmediately be separated 431 and a determination 433 made to confirmwhether the candidate signal is a cardiac signal, before returning 444to the master ITCS routine that called the signal source separationprocess.

[0089] If there is no clear candidate eigenvalue, or if the largestvalue eigenvalue did not provide a signal of interest, an iterativeprocess may be used to separate 432 and search 436 for the signal ofinterest (e.g., cardiac signal). This process 432, 436, 434 can berepeated until such a signal is found, or no more signals are separable434 as determined by exceeding a predefined number of iterations N_(max)or some other termination criterion. An example of such a criterion isan eigenvalue considered at the current iteration being proportionatelysmaller than the largest eigenvalues by some predetermined amount.

[0090] If the iterations 434 are completed and a cardiac signal is notfound at 436, then an Independent component analysis 435 may beattempted to further process the signals in an attempt to find thecardiac signal. If a cardiac signal is still not found at decision 437,after exhausting all possibilities, then a set of default settings 439may be used, or an error routine may be initiated.

[0091] With continued reference to FIGS. 3 through 6, one illustrativesignal source separation methodology according to the present inventionis described below. Such an approach is particularly well-suited for usein an ITCS system. It is to be understood that the example providedbelow is provided for non-limiting, illustrative purposes only.Moreover, it is understood that signal source separation within thecontext of the present invention need not be implemented using thespecific processes described below, or each and every process describedbelow.

[0092] A collected signal is preferably pre-filtered to suppress broadlyincoherent noise and to generally optimize the signal-to-noise ratio(SNR). Any noise suppression in this step has the additional benefit ofreducing the effective number of source signals that need to beseparated.

[0093] A Principal Component Analysis (PCA) is performed on thecollected and/or pre-filtered signal, producing a set of eigenvectorsand associated eigenvalues describing the optimal linear combination, ina least-squares sense, of the recorded signals that makes the componentscoming from different sources orthogonal to one another. As anintermediate step to performing the PCA, an estimate of the spatialcovariance matrix may be computed and averaged over a relatively shorttime interval (on the order of 2-3 beats) to enhance those componentsthat are mutually correlated.

[0094] Each eigenvalue corresponds to the power of the signal projectedalong the direction of each associated eigenvector. The cardiac signalcomponent is typically identified by one of the largest eigenvalues.Occasionally, PCA does not achieve a substantially sufficient level ofsource independence. In such a case, an Independent Component Analysis(ICA) may be performed to determine the actual source direction, eitherupon the PCA-transformed signal, or directly upon the collected signal.The ICA consists of a unitary transformation based on higher-orderstatistical analysis. For example, separation of two mixed sources maybe achieved by rotating the complex variable formed from the signals onan angle that aligns their probability distributions with basis vectors.In another approach, an algorithm based on minimization of mutualinformation between components, as well as other approaches generallyknown in the field of ICA, may be used to achieve reconstructed sourceindependence.

[0095]FIG. 7 graphically depicts SNR improvement achievable by a signalsource separation methodology of the present invention. In thisillustrative example, data was gathered under low-SNR conditions withelectrocautery noise using seven electrodes implanted in the thoracicregion of a pig. The bottom subplot, identified as trace 452, representsthe raw implanted electrode signal. The next subplot, identified astrace 450, shows this signal after input filtering for optimal raw SNRusing a linear-phase (4^(th)-order Bessel) band pass filter from 5 to 20Hz. The top two subplots, identified as trace 448 and trace 446,illustrate the resulting separated components associated with the twolargest eigenvalues. In this example, trace 446 is associated with theelectrocautery signal, having the largest eigenvalue. Trace 448 is theuncorrupted cardiac signal.

[0096] An ITCS device may, for example, employ a hierarchicaldecision-making procedure that initiates a blind source separationalgorithm when noise or arrhythmia is detected. By way of example, alocal peak density algorithm or a curvature-based significant pointmethodology may be used as a high-level detection routine.

[0097] The ITCS device may compute an estimate of the covariance matrix.It may be sufficient to compute the covariance matrix for only a shorttime. Computation of the eigenvalues and eigenvectors required for thePCA may also be performed adaptively through an efficient updatingalgorithm.

[0098] The cardiac signal can be identified among the few (e.g., two orthree) largest separated signals. One of several known algorithms may beused. For example, local peak density (LPD) or beat detection (BD)algorithms may be used. The LPD algorithm can be used to identify thecardiac signal by finding a signal that has an acceptable physiologicrange of local peak densities by comparing the LPD to a predeterminedrange of peak densities known to be acceptable. The BD algorithm willfind a signal that has a physiologic range of beat rate. In the casewhere two signals look similar, a morphology algorithm may be used forfurther discrimination. It may be beneficial to use the same algorithmat different levels of hierarchy: 1) initiation of blind sourceseparation algorithm; 2) iterative identification of a cardiac signal.

[0099] Mathematical development of an exemplary blind source separationalgorithm in accordance with the present invention is provided asfollows. Assume there are m source signals s₁(t), . . . , s_(m)(t) thatare detected inside of the body, comprising a desired cardiac signal andsome other independent noise, which may, for example, includemyopotential noise, electrocautery response, etc. These signals arerecorded simultaneously from k sensing vectors derived from subcutaneoussensing electrodes, where k>m in a preferred approach. By definition,the signals are mixed together into the overall voltage gradient sensedacross the electrode array. In addition, there is usually an additivenoise attributable, for example, to environmental noise sources. Therelationship between the source signals s(t) and recorded signals x(t)is described below: $\begin{matrix}{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix} = {\begin{pmatrix}{y_{1}(t)} \\{y_{2}(t)} \\\vdots \\{y_{k}(t)}\end{pmatrix} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\\vdots \\{n_{k}(t)}\end{pmatrix}}} \\{= {{\begin{pmatrix}a_{11} & a_{12} & \ldots & a_{1m} \\a_{21} & a_{22} & \ldots & a_{2m} \\\vdots & \vdots & ⋰ & \vdots \\a_{k1} & a_{k2} & \ldots & a_{k\quad m}\end{pmatrix}\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\\vdots \\{s_{m}(t)}\end{pmatrix}} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\\vdots \\{n_{k}(t)}\end{pmatrix}}} \\{= {x(t)}} \\{= {{y(t)} + {n(t)}}} \\{= \begin{matrix}{{{{As}(t)} + {n(t)}},} & \quad & {m < k}\end{matrix}}\end{matrix}$

[0100] Here, x(t) is an instantaneous linear mixture of the sourcesignals and additive noise, y(t) is the same linear mixture without theadditive noise, n(t) is environmental noise modeled as Gaussian noise, Ais an unknown mixing matrix, and s(t) are the unknown source signalsconsidered here to comprise the desired cardiac signal and otherbiological artifacts. There is no assumption made about the underlyingstructure of the mixing matrix and the source signals, except for theirspatial statistical independence. The objective is to reconstruct thesource signals s(t) from the recorded signals x(t).

[0101] Reconstruction of the source signals s(t) from the recordedsignals x(t) preferably involves pre-filtering x(t) to optimize the SNR(i.e., maximize the power of s(t) against that of n(t)). Here, a linearphase filter can be used to minimize time-domain dispersion (tails andringing) and best preserve the underlying cardiac signal morphology. Itis noted that the notation x(t) is substituted for the pre-filteredversion of x(t).

[0102] An estimate of the spatial covariance matrix R is formed as shownimmediately below. This step serves to enhance the components of thesignal that are mutually correlated and downplays incoherent noise.$\begin{matrix}{R = {\frac{1}{T_{({{\sim 1}\quad \sec})}}{\sum\limits_{{t = 1},T}{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\ldots \\{x_{k}(t)}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} & {x_{2}(t)} & \ldots & {x_{k}(t)}\end{pmatrix}}}}} \\{= {\frac{1}{T_{({{\sim 1}\quad \sec})}}{\sum\limits_{{t = 1},T}\begin{bmatrix}{{x_{1}(t)}*{x_{1}(t)}} & {{x_{1}(t)}*{x_{2}(t)}} & \ldots & {{x_{1}(t)}*{x_{k}(t)}} \\{{x_{2}(t)}*{x_{1}(t)}} & {{x_{2}(t)}*{x_{2}(t)}} & \ldots & {{x_{2}(t)}*{x_{k}(t)}} \\\ldots & \ldots & ⋰ & \ldots \\{{x_{k}(t)}*{x_{1}(t)}} & {{x_{k}(t)}*{x_{2}(t)}} & \ldots & {{x_{k}(t)}*{x_{k}(t)}}\end{bmatrix}}}}\end{matrix}$

[0103] Eigenvalues and eigenvectors of the covariance matrix R may bedetermined using singular value decomposition (SVD). By definition, theSVD factors R as a product of three matrices R=USV^(T), where U and Vare orthogonal matrices describing amplitude preserving rotations, and Sis a diagonal matrix that has the squared eigenvalues σ₁ . . . σ_(k) onthe diagonal in monotonically decreasing order. Expanded into elements,this SVD may be expressed as follows. $R = {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1k} \\u_{21} & u_{22} & \ldots & u_{2k} \\\vdots & \vdots & ⋰ & \vdots \\u_{k1} & u_{k2} & \ldots & u_{kk}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & 0 & 0 \\0 & \sigma_{2} & 0 & 0 \\\vdots & \vdots & ⋰ & \vdots \\0 & 0 & \ldots & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\\vdots & \vdots & ⋰ & \vdots \\v_{k1} & v_{k2} & \ldots & v_{kk}\end{pmatrix}}$

[0104] The columns of matrix V consist of eigenvectors that span a newcoordinate system wherein the components coming from different sourcesare orthogonal to one another. Eigenvalues σ₁. . . σ_(k) correspondrespectively to columns 1 . . . k of V. Each eigenvalue defines thesignal “power” along the direction of its corresponding eigenvector. Thematrix Vthus provides a rotational transformation of x(t) into a spacewhere each separate component of x is optimally aligned, in aleast-squares sense, with a basis vector of that space.

[0105] The largest eigenvalues correspond to the highest powercomponents, which typically represent the mixed source signals y₁(t), .. . ,y_(m)(t). The lower eigenvalues typically are associated withadditive noise n₁(t), . . . ,n_(k-m)(t). Each eigenvector may then beviewed as an optimal linear operator on x that maximizes the power ofthe corresponding independent signal component. As a result, thetransformed signal is found as: ${\hat{y}(t)} = {\begin{pmatrix}{{\hat{y}}_{1}(t)} \\\vdots \\{{\hat{y}}_{m}(t)}\end{pmatrix} = {\begin{pmatrix}v_{11} & v_{21} & \ldots & v_{k1} \\\vdots & \vdots & ⋰ & \vdots \\v_{1m} & v_{2m} & \ldots & v_{k\quad m}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix}}}$

[0106] The component estimates ŷ₁(t), . . . , ŷ_(m)(t) of y₁(t), . . . ,y_(m)(t) are aligned with the new orthogonal system of coordinatesdefined by eigenvectors. As a result, they should be orthogonal to eachother and thus independent.

[0107] In an alternative implementation, eigenvalues and eigenvectors ofthe covariance matrix R may be determined using eigenvalue decomposition(ED). By definition, the ED solves the matrix equation RV=SV so that Sis a diagonal matrix having the eigenvalues σ₁ . . . σ_(k) on thediagonal, preferably in monotonically decreasing order, and so thatmatrix V contains the corresponding eigenvectors along its columns. Theresulting eigenvalues and associated eigenvectors may be applied insimilar manner to those resulting from the SVD of covariance matrix R.

[0108] In an alternative implementation, eigenvalues and eigenvectorsare computed directly from x(t) by forming a rectangular matrix X of ksensor signals collected during a time segment of interest, andperforming an SVD directly upon X. The matrix X and its decompositionmay be expressed as follows. $X = {\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix} = {\begin{pmatrix}{x_{1}\left( t_{1} \right)} & {x_{1}\left( t_{2} \right)} & \ldots & {x_{1}\left( t_{T} \right)} \\{x_{2}\left( t_{1} \right)} & {x_{2}\left( t_{2} \right)} & \cdots & {x_{2}\left( t_{T} \right)} \\\vdots & \vdots & ⋰ & \vdots \\{x_{k}\left( t_{1} \right)} & {x_{k}\left( t_{2} \right)} & \cdots & {x_{k}\left( t_{T} \right)}\end{pmatrix} = {USV}^{T}}}$

[0109] Note that in cases where T>k, a so-called “economy-size” SVD maybe used to find the eigenvalues and eigenvectors efficiently. Such anSVD may be expressed as follows, expanded into elements. $\begin{matrix}{X = {USV}^{T}} \\{= {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1T} \\u_{21} & u_{22} & \ldots & u_{2T} \\\vdots & \vdots & ⋰ & \vdots \\u_{k1} & u_{k2} & \ldots & u_{kT}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & \ldots & 0 \\0 & \sigma_{2} & \ldots & 0 \\\vdots & \vdots & ⋰ & \vdots \\0 & 0 & \ldots & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\\vdots & \vdots & ⋰ & \vdots \\v_{k1} & v_{k2} & \ldots & v_{kk}\end{pmatrix}}}\end{matrix}$

[0110] A similar economy-sized SVD may also be used for the less typicalcase where k>T. The matrices S and V resulting from performing the SVDof data matrix X may be applied in the context of this present inventionidentically as the matrices S and V resulting from performing the SVD onthe covariance matrix R.

[0111] At this point, the mutual separation of ŷ₁(t), . . . , ŷ_(m)(t)would be completed, based on the covariance statistics. Occasionally,information from covariance is not sufficient to achieve sourceindependence. This happens, for example, when the cardiac signal iscorrupted with electrocautery, which may cause perturbations from thelinearly additive noise model. In such a case, Independent ComponentAnalysis (ICA)can be used to further separate the signals.

[0112] The ICA seeks to find a linear transformation matrix W thatinverts the mixing matrix A in such manner as to recover an estimate ofthe source signals. The operation may be described as follows.${s(t)} = {\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\\vdots \\{s_{m}(t)}\end{pmatrix} = {{W\quad {y(t)}} \approx {A^{- 1}{y(t)}}}}$

[0113] Here we substitute s(t) for the recovered estimate of the sourcesignals. The signal vector y(t) corresponds to either the collectedsensor signal vector x(t) or to the signal ŷ(t) separated with PCA. Thematrix W is the solution of an optimization problem that maximizes theindependence between the components s₁(t), . . . , s_(m)(t) ofs(t)=Wy(t). We treat the components of s(t) as a vector of randomvariables embodied in the vector notation s, so that the desiredtransformation would optimize some cost function C(s)=C([s₁(t), . . . ,s_(m)(t)]) that measures the mutual independence of these components.Given the joint probability density function (pdf) f(s) and thefactorized pdf {overscore (ƒ)}(S)=ƒ₁(s₁)ƒ₂(s₂) . . . ƒ_(m)(s_(m)), orgiven estimates of these pdf's, we may solve the following.${\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{D\left( {{f(s)},{\overset{\_}{f}(s)}} \right)}{s}}}}$

[0114] The function D(ƒ(s), {overscore (ƒ)}(s)) may be understood as astandard distance measure generally known in the art, such as forexample an absolute value difference |ƒ(s)−{overscore (ƒ)}(s)|,Euclidean distance (ƒ(s)−{overscore (ƒ)}(s))², or p-norm(ƒ(s)−{overscore (ƒ)}(s))^(p). The distance measure approaches zero asƒ(s) approaches {overscore (ƒ)}(s), which by the definition ofstatistical independence, occurs as the components of s approach mutualstatistical independence.

[0115] In an alternative implementation, the distance measure may takethe form of a Kullback-Liebler divergence (KLD) between ƒ(s) and{overscore (ƒ)}(s), yielding cost function optimizations in either ofthe following forms. $\begin{matrix}{{\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{f(s)}\quad \log \quad \frac{f(s)}{\overset{\_}{f}(s)}{s}}}}} \\{or} \\{\quad {= {\begin{matrix}\min \\W\end{matrix}{\int{{\overset{\_}{f}(s)}\quad \log \quad \frac{\overset{\_}{f}(s)}{f(s)}{s}}}}}}\end{matrix}$

[0116] Since the KLD is not symmetric, the two alternative measures arerelated but not precisely equal. One measure could be chosen, forexample, if a particular underlying data distribution favors convergencewith that measure.

[0117] Several alternative approaches may be used to measure the mutualindependence of the components of s. These may include the maximumlikelihood method, maximization of negentropy or its approximation, andminimization of mutual information.

[0118] In the maximum likelihood method, the desired matrix W is foundas a solution of the following optimization problem, $\begin{matrix}{{{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log \quad {f_{i}\left( {s_{i}\left( t_{j} \right)} \right)}}}}} + {T\quad \log \quad {{\det \quad W}}}} = {{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log \quad f_{i}\left( {w_{i}^{T}{y\left( t_{j} \right)}} \right)}}}} +}} \\{{T\quad \log \quad {{\det \quad W}}}}\end{matrix}$

[0119] where w_(i) are columns of the matrix W. In the negentropymethod, the cost function is defined in terms of differences in entropybetween s and a corresponding Gaussian random variable, resulting in thefollowing optimization problem,${\max\limits_{W}\left\{ {{H\left( s_{gauss} \right)} - {H(s)}} \right\}} = {\max\limits_{W}\left\{ {{- {\int{{f\left( s_{gauss} \right)}\log \quad {f\left( s_{gauss} \right)}{s_{gauss}}}}} + {\int{{f(s)}{\log (s)}{s}}}} \right\}}$

[0120] where H(s) is the entropy of random vector s, and s_(gauss) is aGaussian random vector chosen to have a covariance matrix substantiallythe same as that of s.

[0121] In the minimization of mutual information method, the costfunction is defined in terms of the difference between the entropy of sand the sum of the individual entropies of the components of s,resulting in the following optimization problem$\min\limits_{W}\left\{ {{- \quad {\sum\limits_{i = 1}^{m}{\int{{f\left( s_{i} \right)}\quad \log \quad {f\left( s_{i} \right)}{s_{i}}}}}} + {\int{{f(s)}\quad \log \quad {f(s)}{s}}}} \right\}$

[0122] All preceding cost function optimizations having an integral formmay be implemented using summations by approximating the underlying pdfs with discrete pdf's, for example as the result of estimating the pdfusing well-known histogram methods. We note that knowledge of the pdf,or even an estimate of the pdf, can be difficult to implement inpractice due either to computational complexity, sparseness of availabledata, or both. These difficulties may be addressed using cost functionoptimization methods based upon kurtosis, a statistical parameter thatdoes not require a pdf.

[0123] In an alternative method a measure of independence could beexpressed via kurtosis, equivalent to the fourth-order statistic definedas the following for the i^(th) component of s

kurt(s _(i))=E{s _(i) ⁴}−3(E{s _(i) ²})²

[0124] In this case W is found as a matrix that maximizes kurtosis ofs=Wy over all the components of s (understanding y to be a vector ofrandom variables corresponding to the components of y(t)). In all theprevious examples of ICA optimization the solution W could be found vianumerical methods such as steepest descent, Newton iteration, etc., wellknown and established in the art. These methods could prove numericallyintensive to implement in practice, particularly if many estimates ofstatistics in s must be computed for every iteration in W.

[0125] Computational complexity can be addressed by several means. Tobegin, the ICA could be performed on the PCA-separated signal ŷ(t) withthe dimensionality reduced to only the first few (or in the simplestcase, two) principal components. For situations where two principalcomponents are not sufficient to separate the sources, the ICA couldstill be performed pairwise on two components at a time, substitutingcomponent pairs at each iteration of W (or group of iterations of W).

[0126] In one example, a simplified two-dimensional ICA may be performedon the PCA separated signals. In this case, a unitary transformationcould be found as a Givens rotation matrix with rotation angle θ,${W(\theta)} = \begin{pmatrix}{\cos \quad \theta} & {\sin \quad \theta} \\{{- \sin}\quad \theta} & {\cos \quad \theta}\end{pmatrix}$

[0127] where s(t)=W(θ)y(t). Here W(θ) maximizes the probabilitydistribution of each component along the basis vectors, such that thefollowing is satisfied.$\theta = {\arg \quad {\max\limits_{\theta}{\sum\limits_{t = 1}^{T}\quad {\log \quad {f\left( {s(t)} \middle| \theta \right)}}}}}$

[0128] This optimal rotation angle may be found by representing vectorsy(t) and s(t)

ξ=e ^(i4θ) E(ρ⁴ e ^(i4θ′))=e ^(i4θ) E[(s ₁ +is ₂)⁴ ]=e ^(i4θ)(κ₄₀^(s)+κ₀₄ ^(s))

[0129] as complex variables in the polar coordinate formy=y₁+iy₂=ρe^(iρ), s=s₁+is₂=ρe^(iφ′) and finding the relationshipsbetween their phase angles φ, φ′:φ=φ′+θ, where θ is the rotation thatrelates the vectors. Then, the angle θ may be found from the fourthorder-statistic of a complex variable ξ, where κ^(s) is kurtosis of thesignal s(t).

[0130] By definition, source kurtosis is unknown, but may be found basedon the fact that the amplitude of the source signal and mixed signalsare the same.

[0131] As a result, 4θ={circumflex over (ξ)}sign({circumflex over (γ)})

with γ=E[ρ ⁴]−8=κ₄₀ ^(s)+κ₀₄ ^(s) and ρ² =s ₁ ² +s ₂ ² =y ₁ ² +y ₂ ²

[0132] In summary, the rotation angle can be estimated as:$\theta = {\frac{1}{4}\quad {angle}\quad \left( {\hat{\xi}\quad {sign}\quad \left( \hat{\gamma} \right)} \right)\quad {where}}$${\hat{\xi} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}{\rho_{t}^{4}^{\quad 4\quad {\phi {(t)}}}}}} = {\frac{1}{T}{\sum\limits_{{t = 1},T}\left( {{y_{1}(t)} + {i\quad {y_{2}(t)}}} \right)^{4}}}}},{\hat{\gamma} = {{{\frac{1}{T}{\sum\limits_{{t = 1},T}\rho_{t}^{4}}} - 8} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}\left( {{y_{1}^{2}(t)} + {i\quad {y_{2}^{2}(t)}}} \right)^{4}}} - 8}}}$

[0133] After the pre-processing step, the cardiac signal is normally thefirst or second most powerful signal. In addition, there is usually inpractice only one source signal that is temporally white. In this case,rotation of the two-dimensional vector y=y₁+iy₂=ρe^(iφ) is all that isrequired. In the event that more than two signals need to be separated,the Independent Component Analysis process may be repeated in pair-wisefashion over the m(m−1)/2 signal pairs until convergence is reached,usually taking about (1+{square root}{square root over (m)})iterations.

[0134] An ITCS device that implements the above-described processes mayrobustly separate the cardiac signal from a low SNR signal recorded fromthe implantable device. Such an ITCS device robustly separates cardiacsignals from noise to allow for improved sensing of cardiac rhythms andarrhythmias.

[0135] The system operates by finding a combination of the spatiallycollected low SNR signals that makes cardiac signal and noise orthogonalto each other (independent). This combination achieves relatively cleanextraction of the cardiac signal even from negative SNR conditions.

[0136] An ITCS device may operate in a batch mode or adaptively,allowing for on-line or off-line implementation. To save power, thesystem may include the option for a hierarchical decision-making routinethat uses algorithms known in the art for identifying presence ofarrhythmias or noise in the collected signal and turning on the cardiacsignal extraction routine.

[0137] Various modifications and additions can be made to the preferredembodiments discussed hereinabove without departing from the scope ofthe present invention. Accordingly, the scope of the present inventionshould not be limited by the particular embodiments described above, butshould be defined only by the claims set forth below and equivalentsthereof.

What is claimed is:
 1. A signal separation method, comprising: detecting a plurality of composite signals at a plurality of subcutaneous non-intrathoracic locations, the plurality of composite signals associated with a plurality of sources; separating a signal from the plurality of composite signals using blind source separation; and identifying the separated signal as a cardiac signal.
 2. The method of claim 1, further comprising iteratively separating signals from the plurality of composite signals until the cardiac signal is identified.
 3. The method of claim 1, wherein the plurality of composite signals comprises the cardiac signal and at least one non-cardiac signal.
 4. The method of claim 1, wherein the blind source separation comprises a principal component analysis.
 5. The method of claim 4, wherein the principal component analysis includes a singular value decomposition.
 6. The method of claim 4, wherein the principal component analysis includes an eigenvalue decomposition.
 7. The method of claim 1, wherein the blind source separation comprises an independent component analysis.
 8. The method of claim 1, wherein the blind source separation comprises a principal component analysis and an independent component analysis.
 9. The method of claim 1, further comprising filtering each of the plurality of composite signals before separating the signal.
 10. The method of claim 1, further comprising band-pass filtering each of the plurality of composite signals.
 11. The method of claim 1, further comprising determining a cardiac condition using the cardiac signal.
 12. The method of claim 1, further comprising detecting a cardiac condition using the separated signal, wherein detecting the cardiac condition comprises performing a rate based analysis of the cardiac signal.
 13. The method of claim 1, further comprising detecting a cardiac condition using the separated signal, wherein detecting the cardiac condition comprises performing a morphology based analysis of the cardiac signal.
 14. The method of claim 1, further comprising detecting a cardiac condition using the separated signal, wherein detecting the cardiac condition comprises performing a pattern and rate based analysis of the cardiac signal.
 15. The method of claim 1, further comprising detecting a cardiac condition using the cardiac signal and implantably treating the cardiac condition.
 16. The method of claim 15, wherein implantably treating the cardiac condition comprises delivering a cardiac stimulation therapy.
 17. The method of claim 15, wherein implantably treating the cardiac condition comprises delivering a cardiac stimulation therapy using an implanted subcutaneous non-intrathoracic electrode.
 18. The method of claim 15, wherein detecting the plurality of composite signals at the plurality of subcutaneous locations comprises using a subcutaneous non-intrathoracic electrode array and wherein implantably treating the cardiac condition comprises using the electrode array to provide a cardiac stimulation therapy.
 19. The method of claim 1, further comprising: forming a composite signal matrix from the plurality of composite signals; and performing a principal component analysis on the composite signal matrix, thereby producing a set of eigenvalues and associated eigenvectors.
 20. The method of claim 19, wherein an eigenvector of the associated eigenvectors that is associated with a largest magnitude eigenvalue of the set of eigenvalues is used to separate the signal from the plurality of composite signals.
 21. The method of claim 20, wherein the signal is separated from the plurality of composite signals by multiplying the composite signal matrix by the eigenvector.
 22. The method of claim 20, wherein the signal is separated iteratively from the plurality of composite signals using an eigenvector associated with a next-largest magnitude eigenvalue for each iteration, until the cardiac signal is identified.
 23. The method of claim 22, wherein the cardiac signal is identified using a local peak density of the separated signal, wherein the local peak density is within a predetermined range.
 24. The method of claim 22, wherein the cardiac signal is identified using beat detection on the separated signal, wherein a beat rate is within a predetermined range.
 25. The method of claim 22, wherein the cardiac signal is identified using a local rate of occurrence of significant points in the separated signal, wherein the local rate of occurrence is within a predetermined range.
 26. The method of claim 22, wherein the cardiac signal is identified using a morphology of the separated signal, wherein the morphology satisfies a physiological characteristic.
 27. The method of claim 19, further comprising forming an intermediate signal matrix by multiplying the composite signal matrix by a matrix composed of the eigenvectors corresponding to at least the two largest eigenvalues, and finding a unitary matrix corresponding to a rotational transformation of the intermediate signal matrix that increases the independence of the intermediate signals.
 28. The method of claim 27, further comprising forming an independent signal matrix by multiplying the intermediate signal matrix by the unitary matrix, wherein the independent signal matrix comprises a set of independent signal vectors.
 29. The method of claim 28, wherein a signal vector from the set of independent signal vectors is iteratively examined until a cardiac signal is identified.
 30. The method of claim 29, wherein the cardiac signal is identified using a local peak density of the examined signal, wherein the local peak density is within a predetermined range.
 31. The method of claim 29, wherein the cardiac signal is identified using beat detection on the examined signal, wherein a beat rate is within a predetermined range.
 32. The method of claim 29, wherein the cardiac signal is identified using a local rate of occurrence of significant points in the examined signal, wherein the local rate of occurrence is within a predetermined range.
 33. The method of claim 29, wherein the cardiac signal is identified using a morphology of the examined signal, wherein the morphology satisfies a physiological characteristic.
 34. The method of claim 1, further comprising forming an estimate of a spatial covariance matrix for a composite signal matrix formed from the plurality of composite signals.
 35. The method of claim 34, further comprising performing a principal component analysis on the estimate of the spatial covariance matrix, producing a set of eigenvalues and associated eigenvectors.
 36. The method of claim 35, wherein an eigenvector of the associated eigenvectors that is associated with a largest magnitude eigenvalue of the set of eigenvalues is used to separate the signal from the plurality of composite signals.
 37. The method of claim 36, wherein the signal is separated from the plurality of composite signals by multiplying the composite signal matrix by the eigenvector.
 38. The method of claim 36, wherein the signal is separated iteratively from the plurality of composite signals using an eigenvector associated with a next-largest magnitude eigenvalue for each iteration, until the cardiac signal is identified.
 39. The method of claim 38, wherein the cardiac signal is identified using a local peak density of the separated signal, wherein the local peak density is within a predetermined range.
 40. The method of claim 38, wherein the cardiac signal is identified using beat detection on the separated signal, wherein a beat rate is within a predetermined range.
 41. The method of claim 38, wherein the cardiac signal is identified using a local rate of occurrence of significant points in the separated signal, wherein the local rate of occurrence is within a predetermined range.
 42. The method of claim 38, wherein the cardiac signal is identified using a morphology of the separated signal, wherein the morphology satisfies a physiological characteristic.
 43. The method of claim 35, further comprising forming an intermediate signal matrix by multiplying the composite signal matrix by a matrix composed of the eigenvectors corresponding to at least the two largest eigenvalues, and finding a unitary matrix corresponding to a rotational transformation of the intermediate signal matrix that increases the independence of the intermediate signals.
 44. The method of claim 43, further comprising forming an independent signal matrix by multiplying the intermediate signal matrix by the unitary matrix, wherein the independent signal matrix comprises a set of independent signal vectors.
 45. The method of claim 44, wherein a signal vector from the set of independent signal vectors is iteratively examined until a cardiac signal is identified.
 46. The method of claim 45, wherein the cardiac signal is identified using a local peak density of the examined signal, wherein the local peak density is within a predetermined range.
 47. The method of claim 45, wherein the cardiac signal is identified using beat detection on the examined signal, wherein a beat rate is within a predetermined range.
 48. A signal separation method, comprising: detecting, using a device implanted within subcutaneous non-intrathoracic tissue, a plurality of composite signals at a plurality of locations, the composite signals produced by a plurality of sources; filtering the detected composite signals; separating a signal from the filtered signals; and determining a cardiac condition using the separated signal.
 49. The method of claim 48, wherein filtering comprises performing a spatial correlation of the plurality of composite signals.
 50. The method of claim 48, wherein filtering comprises filtering the plurality of composite signals prior to separating the signal.
 51. The method of claim 48, wherein filtering comprises using a band-pass filter on the plurality of composite signals.
 52. The method of claim 48, further comprising forming an estimate of a spatial covariance matrix for the plurality of composite signals.
 53. The method of claim 48, wherein separating the signal from the filtered signals comprises identifying the separated signal as a cardiac signal or a non-cardiac signal.
 54. The method of claim 48, wherein separating the signal from the filtered signals comprises performing a principal component analysis.
 55. The method of claim 54, wherein the principal component analysis produces a set of eigenvalues and associated eigenvectors, and an eigenvector associated with a largest magnitude eigenvalue is used to separate the signal from the filtered signals.
 56. The method of claim 55, wherein the signal is separated iteratively from the plurality of composite signals using a next-largest magnitude eigenvalue for each iteration, until a cardiac signal is separated from the filtered signals.
 57. The method of claim 48, further comprising implantably treating the cardiac condition using the implanted device.
 58. The method of claim 48, wherein the plurality of composite signals comprises a cardiac signal and at least one non-cardiac signal.
 59. An implantable cardiac device, comprising: a plurality of electrodes configured for subcutaneous non-intrathoracic sensing; and a signal processor coupled to the plurality of electrodes and configured to receive a plurality of composite signals associated with a plurality of sources sensed by at least some of the electrodes, the signal processor further configured to separate a signal from the plurality of composite signals and identify the separated signal as a cardiac signal.
 60. The device of claim 59, wherein the signal processor iteratively separates signals from the plurality of composite signals until the cardiac signal is identified.
 61. The device of claim 59, wherein the signal processor comprises a filter configured to filter the plurality of composite signals prior to separating the signal.
 62. The device of claim 59, wherein the signal processor comprises a filter configurable to band-pass filter the plurality of composite signals.
 63. The device of claim 59, wherein the signal processor forms an estimate of a spatial covariance matrix for the plurality of composite signals.
 64. The device of claim 59, wherein the signal processor performs a principal component analysis on the plurality of composite signals to separate the signal from the plurality of composite signals.
 65. The device of claim 64, wherein the signal processor performs the principal component analysis to produce a set of eigenvalues and associated eigenvectors, and the signal processor uses an eigenvector with a largest magnitude eigenvalue to separate the signal from the plurality of composite signals.
 66. The device of claim 65, wherein the signal processor iteratively separates the signal from the plurality of composite signals using a next-largest magnitude eigenvalue for each iteration, until the cardiac signal is identified.
 67. The device of claim 59, wherein the signal processor detects a cardiac condition using the cardiac signal.
 68. The device of claim 67, wherein the signal processor performs a rate based analysis of the separated signal to detect the cardiac condition.
 69. The device of claim 67, wherein the signal processor performs a morphology based analysis of the separated signal to detect the cardiac condition.
 70. The device of claim 59, wherein at least some of the plurality of electrodes are configured for subcutaneous non-intrathoracic energy delivery, the device further comprising an energy delivery system coupled to the at least some of the plurality of electrodes, the energy delivery system delivering a cardiac stimulation therapy to treat the cardiac condition.
 71. The device of claim 59, further comprising at least one lead coupled to the plurality of subcutaneous non-intrathoracic electrodes.
 72. The device of claim 59, further comprising a plurality of leads, wherein at least one of the plurality of leads is coupled to an array of electrodes.
 73. An implantable cardiac device, comprising: a plurality of electrodes configured for subcutaneous non-intrathoracic sensing; and a signal processor coupled to the plurality of electrodes, the signal processor configured to receive a composite signal associated with a plurality of sources sensed by at least two of the electrodes, and to extract a cardiac signal from the plurality of composite signals using blind source separation.
 74. The device of claim 73, further comprising at least one lead coupled to the plurality of subcutaneous non-intrathoracic electrodes.
 75. The device of claim 73, further comprising a plurality of leads coupled to the plurality of subcutaneous non-intrathoracic electrodes.
 76. The device of claim 73, further comprising a plurality of leads, wherein at least one of the plurality of leads is coupled to an array of electrodes.
 77. The device of claim 73, wherein the signal processor further comprises an adaptive filter, the adaptive filter altering its filtering characteristics based on a level of ambient noise.
 78. The device of claim 77, wherein the level of ambient noise is determined using the independent component analysis.
 79. The device of claim 73, wherein the blind source separation includes a principal component analysis that produces a set of eigenvalues and associated eigenvectors, and an eigenvector with a largest magnitude eigenvalue is used to extract the cardiac signal from the plurality of composite signals.
 80. The device of claim 79, wherein a signal is separated iteratively from the plurality of composite signals using a next-largest magnitude eigenvalue for each iteration, until the cardiac signal is extracted from the plurality of composite signals.
 81. An implantable cardiac device, comprising: means for subcutaneously detecting a plurality of composite signals produced by a plurality of sources; means for separating a signal from the plurality of composite signals; and means for identifying the separated signal as a cardiac signal.
 82. The device of claim 81, wherein the separating means performs a principal component analysis on the plurality of composite signals.
 83. The device of claim 81, wherein the separating means produces a set of eigenvalues and associated eigenvectors, and an eigenvector with a largest magnitude eigenvalue is used for separating the signal from the plurality of composite signals.
 84. The device of claim 83, wherein the separating means iteratively separates the signal from the plurality of composite signals using a next-largest magnitude eigenvalue for each iteration, until the cardiac signal is separated from the plurality of composite signals.
 85. The device of claim 81, further comprising means for detecting a cardiac condition using the cardiac signal.
 86. The device of claim 85, further comprising means for treating the cardiac condition. 